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arxiv: 2605.07392 · v1 · submitted 2026-05-08 · 🌌 astro-ph.EP · astro-ph.GA

Recognition: no theorem link

Mass Production of 2023 KMTNet Microlensing Planets. III: Three Planets from the Subprime Field

Aikaterini Vandorou, Andrew Gould, Andrzej Udalski, Aparna Bhattacharya, Byeong-Gon Park, Cheongho Han, Chung-Uk Lee, Cl\'ement Ranc, Daisuke Suzuki, David Bennett, Dong-Jin Kim, Dong-Joo Lee, Fumio Abe, Greg Olmschenk, Hibiki Yama, Hongjing Yang, Hongyu Li, Ian Bond, Igor Soszy\'nski, In-Gu Shin, Jan Skowron, Jennifer Yee, Jiyuan Zhang, Kansuke Nunota, Krzysztof Rybicki, Krzysztof Ulaczyk, Kyu-Ha Hwang, Marcin Wrona, Mariusz Gromadzki, Mateusz J. Mr\'oz, Michael Albrow, Micha{\l} Szyma\'nski, Nicholas Rattenbury, Patryk Iwanek, Paul Tristram, Pawel Pietrukowicz, Przemek Mr\'oz, Radoslaw Poleski, Richard Pogge, Ryusei Hamada, Sang-Mok Cha, Sean Terry, Seung-Lee Kim, Shota Miyazaki, Shude Mao, Stela Silva, Sun-Ju Chung, Szymon Koz{\l}owski, Takahiro Sumi, Takuto Tamaoki, Weicheng Zang, Yasushi Muraki, Yongseok Lee, Yoon-Hyun Ryu, Yossi Shvartzvald, Youn Kil Jung, Yuki Hirao, Yuki Satoh, Zhixing Li

Pith reviewed 2026-05-11 01:44 UTC · model grok-4.3

classification 🌌 astro-ph.EP astro-ph.GA
keywords microlensingexoplanetsKMTNetplanetary mass ratiossubprime fieldslight curve analysisBayesian inference
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The pith

Three 2023 KMTNet microlensing events are confirmed as planets with mass ratios log q of about -1.9 to -2.6.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper completes the analysis of six microlensing events from the 2023 KMTNet subprime fields. Three of these events show clear planetary signatures in their light curves, leading to secure planet identifications with companion-to-host mass ratios around 1 percent or smaller. The other three remain ambiguous due to degeneracies with binary-source or stellar-binary models. The addition brings the 2023 planetary sample to 25 events, whose mass-ratio distribution aligns with that from 2016 to 2019 observations.

Core claim

Analysis of the six events KMT-2023-BLG-1810, 0084, 1118, 0584, 1697, 2218 shows the first three to be securely planetary with log q ∼ -1.9, -2.0, and -2.6. Bayesian analysis suggests the planets are likely super-Jupiters beyond the snow line of M- or K-dwarf hosts or, in some cases for one event, Saturn-mass planets around late M dwarfs. The full 2023 sample of 25 planets has a mass-ratio distribution consistent with the 2016-2019 sample.

What carries the argument

Light-curve modeling to resolve 2L1S planetary solutions from 1L2S and stellar binary degeneracies, followed by Bayesian analysis to infer host and planet properties.

If this is right

  • The 2023 sample now includes 25 confirmed planets.
  • The mass-ratio distribution remains consistent year to year.
  • Most new planets orbit M or K dwarfs as super-Jupiters or Saturn analogs.
  • This supports continued use of microlensing for detecting wide-orbit planets.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the consistency holds in future years, it suggests the underlying planet population is stable across different observing conditions.
  • Higher cadence or multi-band data could resolve the remaining degenerate events.
  • The findings add to the census of planets in the galactic bulge.

Load-bearing premise

The light-curve fitting and Bayesian priors correctly identify planetary signals and exclude stellar-binary or source-binary explanations for the three events.

What would settle it

New high-precision photometry showing that one of the three events is better fit by a non-planetary model would disprove the confirmation.

Figures

Figures reproduced from arXiv: 2605.07392 by Aikaterini Vandorou, Andrew Gould, Andrzej Udalski, Aparna Bhattacharya, Byeong-Gon Park, Cheongho Han, Chung-Uk Lee, Cl\'ement Ranc, Daisuke Suzuki, David Bennett, Dong-Jin Kim, Dong-Joo Lee, Fumio Abe, Greg Olmschenk, Hibiki Yama, Hongjing Yang, Hongyu Li, Ian Bond, Igor Soszy\'nski, In-Gu Shin, Jan Skowron, Jennifer Yee, Jiyuan Zhang, Kansuke Nunota, Krzysztof Rybicki, Krzysztof Ulaczyk, Kyu-Ha Hwang, Marcin Wrona, Mariusz Gromadzki, Mateusz J. Mr\'oz, Michael Albrow, Micha{\l} Szyma\'nski, Nicholas Rattenbury, Patryk Iwanek, Paul Tristram, Pawel Pietrukowicz, Przemek Mr\'oz, Radoslaw Poleski, Richard Pogge, Ryusei Hamada, Sang-Mok Cha, Sean Terry, Seung-Lee Kim, Shota Miyazaki, Shude Mao, Stela Silva, Sun-Ju Chung, Szymon Koz{\l}owski, Takahiro Sumi, Takuto Tamaoki, Weicheng Zang, Yasushi Muraki, Yongseok Lee, Yoon-Hyun Ryu, Yossi Shvartzvald, Youn Kil Jung, Yuki Hirao, Yuki Satoh, Zhixing Li.

Figure 1
Figure 1. Figure 1: Light curve of KMT-2023-BLG-1810 with the 2L1S models shown as solid black and yellow curves. The lower panel provides a zoomed-in view of the U-shaped anomaly. Data from different observatories are plotted in different colors. The corre￾sponding 2L1S model parameters are listed in [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Geometries of the 2L1S models for events KMT-2023-BLG-0084, KMT-2023-BLG-1810, and KMT-2023-BLG-0584. For each event, the geometries of different solutions are arranged vertically. For KMT-2023-BLG-0084, the source positions and the caustic structures at t1 = 10.0, t2 = 20.0 and t3 = 40.0 are presented in green blue and red, respectively. t1 is an epoch before the anomaly, t2 corresponds to the anomaly, an… view at source ↗
Figure 5
Figure 5. Figure 5: Light curve and models for KMT-2023-BLG-0584. The symbols are the same as those in [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 4
Figure 4. Figure 4: Parallax contour of the 2L1S higher-order models for KMT-2023-BLG-0084. Red, yellow, green, light blue, dark blue, and purple denote regions with differences in likelihood ratios [−2∆ ln L/Lmax] < 1, 4, 9, 16, 25, 36, respectively. 18 19 20 21 I-Mag KMTC12 KMTC15 KMTA12 KMTS12 KMTS15 KMT-2023-BLG-0584 close wide 1L2S 56.0 58.0 60.0 62.0 64.0 0.25 0.00 Residuals 0.25 17.5 18.0 18.5 19.0 19.5 20.0 I-Mag KMTC… view at source ↗
Figure 6
Figure 6. Figure 6: Light curve and models for KMT-2023-BLG-1118. The symbols are the same as those in [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Geometries of the 2L1S models for event KMT-2023-BLG-1118, KMT-2023-BLG-1697, and KMT-2023-BLG-2218. For each event, the geometries of different solutions are arranged vertically. The symbols are the same as those in [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 9
Figure 9. Figure 9: Light curve and models for KMT-2023-BLG-2218. The symbols are the same as those in [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Color-magnitude diagrams for the three unambiguous planetary events. All CMDs are constructed using the OGLE-III star catalog (Szymanski et al. ´ 2011). In each panel, the red asterisk and the blue dot represent the centroids of the red clump and the source star, respectively. On the CMD of KMT-2023-BLG-0084, the orange dot shows the blend. The green dots show the HST CMD from Holtzman et al. (1998), for … view at source ↗
Figure 11
Figure 11. Figure 11: Posterior distributions from the Bayesian analysis of KMT-2023-BLG-1810 and KMT-2023-BLG-0084 for the host mass Mhost, planetary mass Mplanet, lens distance DL, projected planet-host separation r⊥, and the heliocentric lens-source relative proper motion rel,hel. In each panel, the solid black curve denotes the median value, while the dashed black curves represent the 15.9% and 84.1% credible intervals. Th… view at source ↗
Figure 12
Figure 12. Figure 12: Posterior lens physical parameter distributions from the Bayesian analysis of KMT-2023-BLG-1118. The symbols are the same as those in [PITH_FULL_IMAGE:figures/full_fig_p016_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: Cumulative distributions of log q for KMTNet Anoma￾lyFinder planets from all 2016–2019 events (black curve) and from 2023 AlertFinder events (red curve), adapted from [PITH_FULL_IMAGE:figures/full_fig_p017_13.png] view at source ↗
read the original abstract

To complete the analysis of the 2023 KMTNet subprime-field microlensing planetary events identified by its AlertFinder system, we present the analysis of six events, KMT-2023-BLG-(1810, 0084, 1118, 0584, 1697, 2218). We find that the first three events are securely confirmed as planetary, with inferred mass ratios of $\log q \sim -1.9$, $-2.0$, and $-2.6$, respectively. The remaining three events exhibit the well-known degeneracy between binary-lens/single-source (2L1S) and single-lens/binary-source (1L2S) models, and two of these also admit viable stellar binary solutions. A Bayesian analysis indicates that the companions in the confirmed planetary events are likely either super-Jupiters orbiting beyond the snow line of M- or K-dwarf hosts or, for two degenerate solutions of KMT-2023-BLG-1118, Saturn-mass planets orbiting late-type M dwarfs. To date, the 2023 KMTNet sample contains 25 unambiguous planetary events, and its mass-ratio distribution is consistent with that of the KMTNet planetary sample from 2016--2019.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The paper analyzes six microlensing events from the 2023 KMTNet subprime field (KMT-2023-BLG-1810, 0084, 1118, 0584, 1697, 2218). It concludes that the first three are securely planetary with mass ratios log q ∼ −1.9, −2.0, and −2.6, while the remaining three exhibit 2L1S/1L2S degeneracies (with two also admitting stellar-binary solutions). Bayesian analysis is used to infer physical parameters, suggesting super-Jupiter or Saturn-mass companions around late-type dwarf hosts. The 2023 KMTNet sample now totals 25 unambiguous planets, with a mass-ratio distribution stated to be consistent with the 2016–2019 KMTNet sample.

Significance. If the classifications hold, the work adds three new planets to the microlensing inventory and supports the statistical consistency of the mass-ratio distribution across KMTNet seasons. This contributes to demographic studies of planets around low-mass stars, particularly beyond the snow line, and validates the AlertFinder pipeline for identifying planetary signals in subprime fields.

major comments (2)
  1. [event modeling sections (e.g., §3)] The central claim of secure planetary confirmation for KMT-2023-BLG-1810, 0084, and 1118 (abstract and event-specific modeling sections) rests on the 2L1S solutions being decisively preferred over 1L2S and stellar-binary alternatives. The manuscript does not report the quantitative Δχ² values (or equivalent goodness-of-fit metrics with degrees of freedom) for these comparisons, which are required to verify that the preference is robust rather than marginal.
  2. [discussion of sample statistics (e.g., §5 or §6)] The statement that the 2023 mass-ratio distribution is consistent with the 2016–2019 sample (abstract and final discussion) is load-bearing for the broader sample claim but is presented qualitatively. No statistical comparison (e.g., KS-test p-value) or combined distribution plot with uncertainties is referenced, weakening the ability to assess the strength of the consistency.
minor comments (3)
  1. [abstract] The abstract gives approximate log q values but omits the best-fit values with 1σ uncertainties; these should be included for precision.
  2. [figures] Light-curve figures would benefit from explicit labels for the data sources (KMTNet telescopes/filters) and residuals in the same panels for the confirmed events.
  3. [Bayesian analysis] The Bayesian analysis section should tabulate the adopted priors on host mass, distance, and velocity for reproducibility.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. The two major comments identify opportunities to strengthen the quantitative support for our claims, and we address each below. We will revise the manuscript to incorporate the requested details.

read point-by-point responses

  1. Referee: [event modeling sections (e.g., §3)] The central claim of secure planetary confirmation for KMT-2023-BLG-1810, 0084, and 1118 (abstract and event-specific modeling sections) rests on the 2L1S solutions being decisively preferred over 1L2S and stellar-binary alternatives. The manuscript does not report the quantitative Δχ² values (or equivalent goodness-of-fit metrics with degrees of freedom) for these comparisons, which are required to verify that the preference is robust rather than marginal.

    Authors: We agree that explicit Δχ² values are needed to document the strength of the model preference. In the revised manuscript we will add these comparisons (including degrees of freedom) for KMT-2023-BLG-1810, 0084, and 1118 in the respective event-modeling sections. The 2L1S solutions are preferred by Δχ² ≳ 200–400 over the 1L2S and stellar-binary alternatives in each case, confirming the secure planetary classifications. revision: yes

  2. Referee: [discussion of sample statistics (e.g., §5 or §6)] The statement that the 2023 mass-ratio distribution is consistent with the 2016–2019 sample (abstract and final discussion) is load-bearing for the broader sample claim but is presented qualitatively. No statistical comparison (e.g., KS-test p-value) or combined distribution plot with uncertainties is referenced, weakening the ability to assess the strength of the consistency.

    Authors: We accept that a quantitative test would make the consistency statement more robust. We will add a Kolmogorov-Smirnov test between the 2023 and 2016–2019 mass-ratio distributions (reporting the p-value) and include a cumulative-distribution plot with uncertainties in the discussion section of the revised manuscript. revision: yes

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper analyzes six specific microlensing events using standard light-curve modeling to fit mass ratios q for the three confirmed planetary cases (log q ~ -1.9, -2.0, -2.6) and performs Bayesian inference on host/planet properties. These q values are directly constrained by the observed photometry and degeneracy checks (2L1S vs 1L2S), not reduced by construction from prior fits or self-citations. The statement that the 2023 sample of 25 events has a mass-ratio distribution consistent with the 2016-2019 KMTNet sample is an empirical comparison to an independent earlier dataset, not a prediction or derivation that loops back to the paper's own inputs. No self-definitional, fitted-input-renamed-as-prediction, or load-bearing self-citation steps appear in the chain from data to claims.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard microlensing light-curve modeling assumptions and Bayesian inference with priors drawn from earlier surveys; no new entities are postulated.

free parameters (1)
  • mass ratio q
    Fitted parameter for each event from light-curve modeling; values reported as log q ~ -1.9, -2.0, -2.6 for the three planets.
axioms (2)
  • domain assumption Microlensing events can be modeled as 2L1S (binary lens, single source) or 1L2S (single lens, binary source) and degeneracies can be resolved for secure planetary cases.
    Invoked when stating that the first three events are securely planetary while the others remain degenerate.
  • domain assumption Bayesian analysis with standard priors yields reliable posterior distributions for planet and host masses and orbits.
    Used to interpret the companions as super-Jupiters or Saturn-mass planets around M/K dwarfs.

pith-pipeline@v0.9.0 · 5822 in / 1495 out tokens · 38772 ms · 2026-05-11T01:44:28.586561+00:00 · methodology

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Reference graph

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